Abstract
Robotic Process Automation (RPA) operates on the user interface (UI) of software applications and automates - by means of a software (SW) robot - mouse and keyboard interactions to remove intensive routine tasks (or simply routines). With the recent advances in Artificial Intelligence, the automation of routines is expected to undergo a radical transformation. Nonetheless, to date, the RPA tools available in the market are not able to automatically learn to automate such routines, thus requiring the support of skilled human experts that observe and interpret how routines are executed on the UIs of the applications. Being the current practice time-consuming and error-prone, in this paper we present SmartRPA, a cross-platform tool that tackles such issues by exploiting UI logs to automatically generate executable RPA scripts that automate the routines enactment by SW robots.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
Notes
- 1.
- 2.
- 3.
XES is the standard for the storage, interchange, and analysis of event logs [15].
- 4.
- 5.
- 6.
- 7.
- 8.
References
van der Aalst, W.M.P., Bichler, M., Heinzl, A.: Robotic process automation. Bus. Inf. Syst. Eng. 60(4), 269–272 (2018)
Agostinelli, S., Maggi, F.M., Marrella, A., Milani, F.: A user evaluation of process discovery algorithms in a software engineering company. In: 2019 IEEE 23rd International Enterprise Distributed Object Computing Conference (EDOC), pp. 142–150 (2019). https://doi.org/10.1109/EDOC.2019.00026
Agostinelli, S., Marrella, A., Mecella, M.: Research challenges for intelligent robotic process automation. In: Di Francescomarino, C., Dijkman, R., Zdun, U. (eds.) BPM 2019. LNBIP, vol. 362, pp. 12–18. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-37453-2_2
Agostinelli, S., Marrella, A., Mecella, M.: Towards Intelligent Robotic Process Automation for BPMers (2020). http://arxiv.org/abs/2001.00804
Aguirre, S., Rodriguez, A.: Automation of a business process using robotic process automation (RPA): a case study. In: Figueroa-García, J.C., López-Santana, E.R., Villa-Ramírez, J.L., Ferro-Escobar, R. (eds.) WEA 2017. CCIS, vol. 742, pp. 65–71. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-66963-2_7
AI-Multiple: All 52 RPA Software Tools & Vendors of 2020: Sortable List (2019). https://blog.aimultiple.com/rpa-tools/
Ayub, A., Wagner, A.R.: Teach Me What You Want to Play: Learning Variants of Connect Four through Human-Robot Interaction (2020). https://arxiv.org/abs/2001.01004
Berti, A., van Zelst, S.J., van der Aalst, W.: Process Mining for Python (PM4Py): Bridging the Gap Between Process- and Data Science (2019). http://arxiv.org/abs/1905.06169
Bisbal, J., Lawless, D., Wu, B., Grimson, J.: Legacy information systems: issues and directions. IEEE Softw. 16(5), 103–111 (1999)
Bosco, A., Augusto, A., Dumas, M., La Rosa, M., Fortino, G.: Discovering automatable routines from user interaction logs. In: Hildebrandt, T., van Dongen, B.F., Röglinger, M., Mendling, J. (eds.) BPM 2019. LNBIP, vol. 360, pp. 144–162. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-26643-1_9
Gao, J., van Zelst, S.J., Lu, X., van der Aalst, W.M.P.: Automated robotic process automation: a self-learning approach. In: Panetto, H., Debruyne, C., Hepp, M., Lewis, D., Ardagna, C.A., Meersman, R. (eds.) OTM 2019. LNCS, vol. 11877, pp. 95–112. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-33246-4_6
Geyer-Klingeberg, J., Nakladal, J., Baldauf, F., Veit, F.: Process mining and robotic process automation: a perfect match. In: 16th International Conference on Business Process Management (BPM 2018), Dissertation/Demos/Industry track (2018)
Han, X., et al.: Automatic Business Process Structure Discovery using Ordered Neurons LSTM: A Preliminary Study (2020). https://arxiv.org/abs/2001.01243
Hill, J., Ford, W.R., Farreras, I.G.: Real conversations with artificial intelligence: a comparison between human-human online conversations and human-chatbot conversations. Comput. Hum. Behav. 49, 245–250 (2015)
IEEE Digital Library: Standard for eXtensible Event Stream (XES) for Achieving Interoperability in Event Logs and Event Streams. IEEE Std 1849–2016 (2016). https://doi.org/10.1109/IEEESTD.2016.7740858
Ito, N., Suzuki, Y., Aizawa, A.: From natural language instructions to complex processes: issues in chaining trigger action rules (2020). https://arxiv.org/abs/2001.02462
Jenkins, P., Wei, H., Jenkins, J.S., Li, Z.: A Probabilistic Simulator of Spatial Demand for Product Allocation (2020). https://arxiv.org/abs/2001.03210
Jimenez-Ramirez, A., Reijers, H.A., Barba, I., Del Valle, C.: A method to improve the early stages of the robotic process automation lifecycle. In: Giorgini, P., Weber, B. (eds.) CAiSE 2019. LNCS, vol. 11483, pp. 446–461. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-21290-2_28
Kirchmer, M.: Robotic Process Automation-Pragmatic Solution or Dangerous Illusion. BTOES Insights, June 17 (2017)
Le, V., Gulwani, S.: FlashExtract: a framework for data extraction by examples. In: ACM SIGPLAN PLDI 2014, pp. 542–553 (2014)
Leno, V., Polyvyanyy, A., Rosa, M.L., Dumas, M., Maggi, F.M.: Action logger: enabling process mining for robotic process automation. In: Proceedings of the Dissertation Award, Doctoral Consortium, and Demonstration Track at 17th International Conference on Business Process Management (BPM 2019), pp. 124–128 (2019)
Leopold, H., van der Aa, H., Reijers, H.A.: Identifying candidate tasks for robotic process automation in textual process descriptions. In: Gulden, J., Reinhartz-Berger, I., Schmidt, R., Guerreiro, S., Guédria, W., Bera, P. (eds.) BPMDS/EMMSAD -2018. LNBIP, vol. 318, pp. 67–81. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-91704-7_5
Levenshtein, V.: Efficient implementation of the levenshtein-algorithm, fault-tolerant search technology, error-tolerant search technologies (2007). http://www.levenshtein.net/
Linn, C., Zimmermann, P., Werth, D.: Desktop activity mining - A new level of detail in mining business processes. In: Workshops der INFORMATIK 2018 - Architekturen, Prozesse, Sicherheit und Nachhaltigkeit, September 26–27, pp. 245–258 (2018)
Marrella, A., Mecella, M., Sardiña, S.: Supporting adaptiveness of cyber-physical processes through action-based formalisms. AI Commun. 31(1), 47–74 (2018). https://doi.org/10.3233/AIC-170748
Miltner, A., et al.: On the fly synthesis of edit suggestions. ACM Program. Lang. 3(OOPSLA), 1–29 (2019)
Acknowledgments
This work has been supported by the “Dipartimento di Eccellenza” grant, the H2020 projects DESTINI and FIRST, the Italian project RoMA - Resilience of Metropolitan Areas, and the Sapienza grant BPbots.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this paper
Cite this paper
Agostinelli, S., Lupia, M., Marrella, A., Mecella, M. (2020). Automated Generation of Executable RPA Scripts from User Interface Logs. In: Asatiani, A., et al. Business Process Management: Blockchain and Robotic Process Automation Forum. BPM 2020. Lecture Notes in Business Information Processing, vol 393. Springer, Cham. https://doi.org/10.1007/978-3-030-58779-6_8
Download citation
DOI: https://doi.org/10.1007/978-3-030-58779-6_8
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-58778-9
Online ISBN: 978-3-030-58779-6
eBook Packages: Computer ScienceComputer Science (R0)